Effects of Crude Oil Properties and Dispersant on the Microstructure and Viscosity of Seawater-in-Oil Emulsions

This study examines the effects of crude oil properties and dispersant concentration (Corexit 9500) on the evolution of bulk viscosity, viscoelastic properties, and microstructure of salt water-in-crude oil emulsions. Microscopy, followed by machine-learning-based analysis, provides the size and spatial distribution of the seawater droplets. The crude oils include light oils. The light and medium oils entrain water up to 80% by volume, and the heavy oils, up to 25%. The droplet sizes and distance between them decrease with increasing viscosity, with small droplets clustering around larger ones. The Bakken- and ANS-based emulsions are unstable, but all of the emulsions evolve in time. All exhibit a non-Newtonian behavior, with the viscosity decreasing with increasing shear rate. The storage modulus is higher than the loss modulus for light oils, and vice versa for heavy oils. Trends of their nondimensional viscosity are collapsed onto two power laws as a function of the Ohnesorge number involving the properties of the original oil, and the size or distance between droplets. For light oils, the power law exponent decreases with increasing capillary number based on the rheometer shear rate and increases for heavy oils. At high shear rates, the exponents converge to the same value, 0.45, suggesting that the oil viscosity becomes the property that defines the emulsion rheology. The present findings are consistent with previously published data. Premixing the emulsions with dispersant causes separation of most of the water from the light oils, leaving only sparse droplet concentrations. In contrast, owing to slow diffusion rate, only a small fraction of the seawater is extracted from the heavy oil emulsions. Hence, the sparse light oil emulsions become Newtonian, but the heavy ones remain non-Newtonian.

Automated summary

This study investigates how the properties of crude oil and dispersant concentration impact the viscosity, viscoelastic properties, and microstructure of salt water-in-crude oil emulsions. Microscopy combined with machine learning analysis is used to determine the size and spatial distribution of seawater droplets. The findings reveal that the size and distance between droplets decrease as viscosity increases, with smaller droplets clustering around larger ones. The emulsions exhibit non-Newtonian behavior, with viscosity decreasing as shear rate increases.